scholarly journals RESEARCH AND GOOGLE TREND FOR HUMAN NEUROPSYCHIATRIC DISORDERS AND MACHINE LEARNING: A BRIEF REPORT

2021 ◽  
Vol 33 (3) ◽  
pp. 354-357
Author(s):  
Manik Sharma ◽  
Keyword(s):  
Machine Learning ◽  
Neuropsychiatric Disorders

Reductionist thinking and animal models in neuropsychiatric research

2019 ◽  
Vol 42 ◽  
Author(s):  
Nicole M. Baran
Keyword(s):  
Animal Models ◽  
Mental Disorders ◽  
Environmental Factors ◽  
Neuropsychiatric Disorders ◽  
Model Organisms ◽  
Developmental Genetic ◽  
Term Study ◽  
Genetic And Environmental Factors ◽  
Mechanisms Of Plasticity

AbstractReductionist thinking in neuroscience is manifest in the widespread use of animal models of neuropsychiatric disorders. Broader investigations of diverse behaviors in non-model organisms and longer-term study of the mechanisms of plasticity will yield fundamental insights into the neurobiological, developmental, genetic, and environmental factors contributing to the “massively multifactorial system networks” which go awry in mental disorders.

Mind wandering as data augmentation: How mental travel supports abstraction

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Mental Content ◽  
Mind Wandering ◽  
Theoretical Framework ◽  
Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Mathematics for Machine Learning

2020 ◽  
Author(s):  
Marc Peter Deisenroth ◽  
A. Aldo Faisal ◽  
Cheng Soon Ong
Keyword(s):  
Machine Learning

Phase Transitions in Machine Learning

2009 ◽  
Author(s):  
Lorenza Saitta ◽  
Attilio Giordana ◽  
Antoine Cornuejols
Keyword(s):  
Machine Learning ◽  
Phase Transitions

Understanding Machine Learning

2009 ◽  
Author(s):  
Shai Shalev-Shwartz ◽  
Shai Ben-David
Keyword(s):  
Machine Learning
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